Amazon
Sr. Applied Scientist, Monetization, Sponsored Products
Amazon, Seattle, Washington, us, 98127
Sr. Applied Scientist, Monetization, Sponsored Products
Job ID: 2821276 | Amazon.com Services LLCAmazon continues to invest heavily in building our world class advertising business. Our products are strategically important to our Retail and Marketplace businesses, driving long term growth. We deliver billions of ad impressions and millions of clicks daily, breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and strong bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. The Sponsored Products Monetization team is broadly responsible for pricing of ads on Amazon search pages, balancing short-term and long-term ad revenue growth to drive sustainable marketplace health.
As a Senior Applied Scientist on our team, you will be responsible for defining the science and technical strategy for one of our most impactful marketplace controls, creating lasting value for Amazon and our advertising customers. You will help to identify unique opportunities to create customized and delightful shopping experience for our growing marketplaces worldwide. Your job will be to identify big opportunities for the team that can help to grow Sponsored Products business working with retail partner teams, Product managers, Software engineers and PMs. You will have the opportunity to design, run and analyze A/B experiments to improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills in an environment that thrives on creativity, experimentation, and product innovation.
Key job responsibilities
Lead science, tech and business strategy and roadmap for Sponsored Products MonetizationDrive alignment across multiple organizations for science, engineering and product strategy to achieve business goalsLead and mentor scientists and engineers across teams to develop, test, launch and improve science models designed to optimize the shopper experience and deliver long term value for Amazon and advertisersDevelop state of the art experimental approaches and ML modelsDrive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexityEstablish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and servingResearch new and innovative machine learning approachesRecruit Scientists to the team and provide mentorship
BASIC QUALIFICATIONS
5+ years of building machine learning models for business application experiencePhD, or Master's degree and 5+ years of applied research experienceExperience programming in Java, C++, Python or related languageExperience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.Experience with large scale distributed systems such as Hadoop, Spark etc.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
Posted:
November 6, 2024 (Updated about 4 hours ago)
#J-18808-Ljbffr
Job ID: 2821276 | Amazon.com Services LLCAmazon continues to invest heavily in building our world class advertising business. Our products are strategically important to our Retail and Marketplace businesses, driving long term growth. We deliver billions of ad impressions and millions of clicks daily, breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and strong bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. The Sponsored Products Monetization team is broadly responsible for pricing of ads on Amazon search pages, balancing short-term and long-term ad revenue growth to drive sustainable marketplace health.
As a Senior Applied Scientist on our team, you will be responsible for defining the science and technical strategy for one of our most impactful marketplace controls, creating lasting value for Amazon and our advertising customers. You will help to identify unique opportunities to create customized and delightful shopping experience for our growing marketplaces worldwide. Your job will be to identify big opportunities for the team that can help to grow Sponsored Products business working with retail partner teams, Product managers, Software engineers and PMs. You will have the opportunity to design, run and analyze A/B experiments to improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills in an environment that thrives on creativity, experimentation, and product innovation.
Key job responsibilities
Lead science, tech and business strategy and roadmap for Sponsored Products MonetizationDrive alignment across multiple organizations for science, engineering and product strategy to achieve business goalsLead and mentor scientists and engineers across teams to develop, test, launch and improve science models designed to optimize the shopper experience and deliver long term value for Amazon and advertisersDevelop state of the art experimental approaches and ML modelsDrive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexityEstablish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and servingResearch new and innovative machine learning approachesRecruit Scientists to the team and provide mentorship
BASIC QUALIFICATIONS
5+ years of building machine learning models for business application experiencePhD, or Master's degree and 5+ years of applied research experienceExperience programming in Java, C++, Python or related languageExperience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.Experience with large scale distributed systems such as Hadoop, Spark etc.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
Posted:
November 6, 2024 (Updated about 4 hours ago)
#J-18808-Ljbffr